Image local dynamic contrast enhancement method and device

Abstract

The invention relates to the technical field of image enhancement, and discloses an image local dynamic contrast enhancement method and device, and the method comprises the steps: carrying out the brightness layering operation of an original image, and obtaining a layered image; performing block operation on the layered image to obtain a plurality of image blocks, performing target filtering on an initial brightness average function corresponding to a first sub-image block in each image block, and then performing brightness mapping and saturation processing on the image blocks based on a target post-filtering function corresponding to the first sub-image block to obtain target image blocks; and the contrast-enhanced image is determined according to all the target image blocks. Therefore, by implementing the method, the local dynamic contrast enhancement process of the image can be realized by performing brightness layering, blocking, initial brightness average function filtering and post-processing operation on the original image, the image contrast enhancement effect is improved, and the image is natural in expression, low in noise and excellent in color expression; and meanwhile, the calculation complexity is reduced.

Description

Technical Field

[0001] The present invention relates to the field of image enhancement technology, and in particular to a method and device for enhancing local dynamic contrast of an image. Background Art

[0002] In the field of image processing, image contrast is a key indicator for measuring image quality. It reflects the brightness difference between the brightest part (white) and the darkest part (black) of the image, and directly affects the visual effect and detail presentation of the image.

[0003] Currently, image contrast enhancement techniques are mainly divided into two categories: global contrast enhancement (GCE) and local contrast enhancement (LCE). Global contrast enhancement focuses on adjusting the contrast of the entire image to improve the overall contrast, and is suitable for situations where the overall brightness and contrast of the image are both weak. However, because these techniques use the entire image as a reference and lack consideration of the image's local characteristics, they have poor scene adaptability. Local contrast enhancement, on the other hand, focuses on adjusting the contrast of local areas of the image to highlight local details. However, existing local contrast enhancement techniques, such as adaptive histogram equalization and adaptive contrast enhancement, suffer from high computational complexity, even over-enhancement, and high noise, limiting their further development and application. Therefore, it is particularly important to provide an image processing technology that can improve contrast enhancement. Summary of the Invention

[0004] The present invention provides a method and device for enhancing local dynamic contrast of an image, which improves the image contrast enhancement effect, makes the image appear natural, has low noise, and has excellent color expression; and reduces the computational complexity at the same time.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a method for enhancing local dynamic contrast of an image, the method comprising:

[0006] Performing a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image;

[0007] Performing a block operation on the layered image to obtain a plurality of image blocks corresponding to the layered image; each of the image blocks includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image;

[0008] For each of the image blocks, determining an initial brightness average function corresponding to the first sub-image block and an average value of texture parameters corresponding to the second sub-image block in the image block, and performing a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block;

[0009] For each of the image blocks, performing a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain a mapped image block, and performing a saturation processing operation on the mapped image block to obtain a target image block;

[0010] According to all the target image blocks, a contrast-enhanced image corresponding to the original image is determined.

[0011] A second aspect of the present invention discloses a device for enhancing local dynamic contrast of an image, the device comprising:

[0012] A layering module, configured to perform a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image;

[0013] a blocking module configured to perform a blocking operation on the layered image to obtain a plurality of image blocks corresponding to the layered image; each of the image blocks includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image;

[0014] a filtering module configured to determine, for each of the image blocks, an initial brightness average function corresponding to the first sub-image block and an average value of texture parameters corresponding to the second sub-image block in the image block, and perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block;

[0015] a post-processing module configured to perform a brightness mapping operation on each of the image blocks using a target filtered function corresponding to the first sub-image block to obtain a mapped image block, and to perform a saturation processing operation on the mapped image block to obtain a target image block;

[0016] A determination module is used to determine the contrast-enhanced image corresponding to the original image based on all the target image blocks.

[0017] As an optional implementation, in the second aspect of the present invention, the manner in which the filtering module determines the initial brightness average function corresponding to the first sub-image block in the image block specifically includes:

[0018] For each first pixel included in the first sub-image block in the image block, determining a multi-order orthogonal transformation function of the brightness value according to the brightness value of the first pixel, and determining a multi-order average orthogonal transformation function of the brightness value according to the multi-order orthogonal transformation function of the brightness value;

[0019] determining a multi-order average orthogonal transformation function of the brightness values ​​of all the first pixels as an initial brightness average function corresponding to the first sub-image block in the image block;

[0020] Wherein, for each first pixel included in the first sub-image block, the multi-order orthogonal transformation function of the brightness value of the first pixel is:

[0021]

[0022] I b is the brightness value of the first pixel, K is a preset normalization constant, and i is a target order index parameter of the brightness value of the first pixel, wherein the value range of i is [0, N], and N is the fitting order of the preset maximum orthogonal basis polynomial;

[0023] And, the average value of the texture parameters corresponding to the second sub-image block is;

[0024]

[0025] T Ω is the total number of pixels in the second sub-image block Ω, and LP(x, y) is the residual value of the second pixel with pixel coordinates (x, y) in the second sub-image block.

[0026] As an optional implementation manner, in the second aspect of the present invention, the filtering module performs a target filtering operation on the initial brightness average function corresponding to the first sub-image block by using the average value of the texture parameters corresponding to the second sub-image block, and a method for obtaining the target filtered function corresponding to the first sub-image block specifically includes:

[0027] For each first pixel included in the first sub-image block, performing an indefinite integral operation on the multi-order orthogonal transformation function of the brightness value of the first pixel according to the multi-order orthogonal transformation function of the brightness value to obtain a multi-order target transformation function of the brightness value;

[0028] determining a cumulative probability distribution function corresponding to the first sub-image block based on a multi-order target transformation function of the brightness values ​​of all the first pixels in the first sub-image block and an initial brightness average function corresponding to the first sub-image block;

[0029] performing a basic filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function to obtain a basic filtered brightness average function corresponding to the first sub-image block, and performing a spatial domain guided filtering operation on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block;

[0030] The multi-order target transformation function of the brightness value is:

[0031]

[0032] And, the cumulative probability distribution function corresponding to the first sub-image block is:

[0033]

[0034] is the initial brightness average function corresponding to the first sub-image block, and M is the maximum brightness value under the bit width corresponding to the first sub-image block.

[0035] As an optional implementation, in the second aspect of the present invention, the filtering module performs a basic filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function, and obtains the basic filtered brightness average function corresponding to the first sub-image block. Specifically, the method includes:

[0036] performing curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to the average value of the texture parameters corresponding to the second sub-image block to obtain a first adjusted function corresponding to the first sub-image block;

[0037] Determining an approximate histogram distribution function corresponding to the first sub-image block according to the first adjusted function, and calculating a first before-and-after mapping brightness difference function corresponding to the first sub-image block according to the first adjusted function and the approximate histogram distribution function;

[0038] Determining a brightness guidance function corresponding to the first sub-image block according to the first before-after mapping brightness difference function, and determining a second before-after mapping brightness difference function corresponding to the first sub-image block according to the brightness guidance function and the first adjusted function;

[0039] determining a mapping mixing coefficient corresponding to the first sub-image block according to the first before-and-after mapping luminance difference function and the second before-and-after mapping luminance difference function, and determining a luminance mixing mapping function corresponding to the first sub-image block according to the mapping mixing coefficient, the luminance guide function, and the first adjusted function;

[0040] performing interval amplitude restriction on the brightness mixing mapping function according to a preset curve restriction region to obtain a restricted mapping function corresponding to the first sub-image block, and fitting a basic filtered brightness average function corresponding to the first sub-image block using the restricted mapping function and a multi-order target transformation function of the brightness values ​​of all the first pixels in the first sub-image block;

[0041] The first adjusted function corresponding to the first sub-image block is:

[0042] C′(I b )=stLp*C(I b )+(1-stLp)I b ;

[0043] The approximate histogram distribution function corresponding to the first sub-image block is:

[0044] H(I b )=C′(I b +1)-C′(I b );

[0045] The brightness difference function before and after the first mapping corresponding to the first sub-image block is:

[0046]

[0047] The brightness guidance function corresponding to the first sub-image block is:

[0048]

[0049] The brightness difference function before and after the second mapping corresponding to the first sub-image block is:

[0050]

[0051] The mapping mixing coefficient corresponding to the first sub-image block is:

[0052]

[0053] The brightness mixing mapping function corresponding to the first sub-image block is:

[0054] C″(I b )=α*C′(Ib )+(1-α)G(I b ).

[0055] As an optional implementation, in the second aspect of the present invention, the filtering module performs a spatially guided filtering operation on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block, specifically comprising:

[0056] Calculating, according to preset window parameters of the target window and the basic filtered brightness average function, the brightness average function within the window corresponding to the first sub-image block and other first sub-image blocks within the target window;

[0057] Calculating a brightness variance parameter corresponding to the first sub-image block according to the basic filtered brightness average function and the windowed brightness average function, and determining a brightness weighting coefficient corresponding to the first sub-image block according to the brightness variance parameter and a preset filter coefficient;

[0058] Determining a target filtered function corresponding to the first sub-image block according to the brightness weighting coefficient, the basic filtered brightness average function, and the windowed brightness average function;

[0059] The brightness average function within the window is:

[0060]

[0061] H is the first side length parameter in the window parameters, L is the second side length parameter in the window parameters, h is the first side length index parameter of the window corresponding to the first sub-image block, l is the second side length index parameter of the window corresponding to the first sub-image block, is the basic filtered brightness average function corresponding to the first sub-image block;

[0062] And, the brightness variance parameter corresponding to the first sub-image block is:

[0063]

[0064] The brightness weighting coefficient corresponding to the first sub-image block is:

[0065]

[0066] Wherein, δ is the filtering coefficient;

[0067] The target filtered function corresponding to the first sub-image block is:

[0068]

[0069] As an optional implementation, in the second aspect of the present invention, the post-processing module performs a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain the mapped image block, specifically comprising:

[0070] Calculating an initial brightness mapping value corresponding to each first pixel according to a target filtered function corresponding to the first sub-image block, a multi-order target transformation function of the brightness value of each first pixel in the first sub-image block, and a pre-acquired low-frequency brightness component of each first pixel;

[0071] For each first pixel in the first sub-image block, calculating a mixed brightness mapping value corresponding to the first pixel based on an initial brightness mapping value, a low-frequency brightness component, and a preset intensity coefficient corresponding to the first pixel, and calculating a target brightness mapping value corresponding to the first pixel based on the mixed brightness mapping value corresponding to the first pixel, a residual value of a corresponding target second pixel, and a preset detail magnification coefficient; the target second pixel being a second pixel included in the second sub-image block in the image block and having the same pixel coordinates as the first pixel;

[0072] performing a brightness mapping operation on the image block according to target brightness mapping values ​​corresponding to all the first pixels in the first sub-image block to obtain a mapped image block;

[0073] For each of the first pixels in the first sub-image block, the initial brightness mapping value corresponding to the first pixel is:

[0074]

[0075] I is the low-frequency brightness component corresponding to the first pixel;

[0076] And, the mixed brightness mapping value corresponding to the first pixel is:

[0077] I fus =(1-γ)*I eq +γ*I;

[0078] γ is the intensity coefficient;

[0079] And, the target brightness mapping value corresponding to the first pixel is:

[0080] I out =I fus +acc*LP;

[0081] acc is the detail magnification coefficient, and LP is the residual value of the target second pixel.

[0082] As an optional implementation, in the second aspect of the present invention, the post-processing module performs a saturation processing operation on the mapped image block to obtain the target image block, specifically comprising:

[0083] Calculating a first saturation parameter of the image block and a second saturation parameter of the mapped image block, and calculating a saturation compensation gain parameter corresponding to the mapped image block based on the first saturation parameter, the second saturation parameter, and a preset saturation enhancement coefficient;

[0084] Determining a maximum blue difference compensation gain parameter corresponding to the mapped image block according to the blue difference chroma component parameter of the image block, and determining a maximum red difference compensation gain parameter corresponding to the mapped image block according to the red difference chroma component parameter of the image block;

[0085] Determining a compensation gain limit parameter corresponding to the mapped image block according to the saturation compensation gain parameter, the maximum blue difference compensation gain parameter, and the maximum red difference compensation gain parameter, and determining a target blue difference compensation gain parameter and a target red difference compensation gain parameter corresponding to the mapped image block according to the compensation gain limit parameter, the blue difference chroma component parameter, and the red difference chroma component parameter;

[0086] performing a saturation processing operation on the mapped image block according to the target blue difference compensation gain parameter and the target red difference compensation gain parameter to obtain a target image block;

[0087] The saturation compensation gain parameter corresponding to the mapped image block is:

[0088]

[0089] ACC satu is the saturation enhancement coefficient, S bf is the first saturation parameter, S af is the second saturation parameter;

[0090] And, the compensation gain limit parameter corresponding to the mapped image block is:

[0091] gain=Min(uv_gain, u_gain, v_gain);

[0092] u_gain is the maximum blue difference compensation gain parameter, and v_gain is the maximum red difference compensation gain parameter;

[0093] And, the target blue difference compensation gain parameter and the target red difference compensation gain parameter corresponding to the mapped image block are respectively:

[0094] U`=U*gain,V`=V*gain;

[0095] U is the blue difference chrominance component parameter, and V is the red difference chrominance component parameter.

[0096] A third aspect of the present invention discloses another device for enhancing local dynamic contrast of an image, the device comprising:

[0097] a memory storing executable program code;

[0098] a processor coupled to the memory;

[0099] The processor calls the executable program code stored in the memory to execute the image local dynamic contrast enhancement method disclosed in the first aspect of the present invention.

[0100] The fourth aspect of the present invention discloses a computer storage medium, wherein the computer storage medium stores computer instructions. When the computer instructions are called, they are used to execute the image local dynamic contrast enhancement method disclosed in the first aspect of the present invention.

[0101] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0102] In an embodiment of the present invention, a brightness layering operation is performed on the original image to obtain a layered image; the layered image is then divided into blocks to obtain multiple image blocks, and the initial brightness average function corresponding to the first sub-image block in each image block is subjected to target filtering. Then, based on the target filtered function corresponding to the first sub-image block, the image blocks are subjected to brightness mapping and saturation processing to obtain target image blocks, thereby determining a contrast-enhanced image based on all target image blocks. It can be seen that the implementation of the present invention can achieve a local dynamic contrast enhancement process for the image by performing brightness layering, block division, filtering of the initial brightness average function, and post-processing operations on the original image, thereby improving the image contrast enhancement effect, making the image appear natural, with low noise, and excellent color performance, while reducing computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0104] Figure 1 This is a flow chart of a method for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention;

[0105] Figure 2 1 is a flow chart of another method for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention;

[0106] Figure 3 This is a schematic structural diagram of a device for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention;

[0107] Figure 4 1 is a schematic structural diagram of another device for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention;

[0108] Figure 5 It is a schematic diagram of a curve restriction area disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0109] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0110] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0111] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0112] The present invention discloses a method and device for enhancing local dynamic contrast of an image, which improves the image contrast enhancement effect, makes the image appear natural, has low noise, and has excellent color expression; and reduces the computational complexity at the same time.

[0113] Example 1

[0114] See also Figure 1 , Figure 1 FIG. 1 is a flow chart of a method for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention. Figure 1 The described method for enhancing local dynamic contrast of images can be applied to a variety of digital images for local dynamic contrast enhancement, such as photos, video frames, medical images, remote sensing images, scanned images, computer graphics, etc., which is not limited in the embodiments of the present invention. Optionally, the method can be implemented by an image contrast enhancement device, which can be integrated into an image processing device, such as a smart computer, smart phone, tablet, camera device, driving recorder, etc., or a local server or cloud server for processing the local dynamic contrast enhancement process of images, which is not limited in the embodiments of the present invention. Figure 1 As shown, the method for enhancing local dynamic contrast of an image may include the following operations:

[0115] 101. Perform a brightness layering operation on the original image to be enhanced to obtain a layered image.

[0116] In the embodiment of the present invention, the layered image includes a base layer image and a residual layer image.

[0117] Furthermore, when the original image is a YUV type image, the brightness layering operation can be performed directly on the original image, and when the original image is an RGB type image, a YUV color gamut space conversion is required to obtain a YUV type image, and then the brightness layering operation is performed on the YUV type image.

[0118] Furthermore, the brightness layering operation can be understood as an unsharp mask operation on the YUV type image, that is, the YUV type image is first blurred to obtain a base layer image. The blurring method can be to take the average value of a fixed window, or the value after Gaussian blur under a fixed window, or other edge-preserving low-pass filtering methods. Then, the blurred image (i.e., the base layer image) is subtracted from the original YUV type image to obtain a residual layer image. It should be noted that the base layer image can be used for local contrast enhancement and can better balance the problem of noise amplification; while the residual layer image can be used for image detail recovery and enhancement.

[0119] 102. Perform a block operation on the layered image to obtain multiple image blocks corresponding to the layered image.

[0120] In an embodiment of the present invention, after the layered image is partitioned, a plurality of image blocks can be obtained, namely, a plurality of first sub-image blocks corresponding to the base layer image and a plurality of second sub-image blocks corresponding to the residual layer. Each image block has a corresponding first sub-image block and a corresponding second sub-image block, namely, each image block includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image, and for each image block, the first sub-image block and the second sub-image block are in a one-to-one correspondence.

[0121] Furthermore, the blocking operation can be understood as dividing the layered image into B*D image blocks. The specific number of blocks can be determined based on the resolution of the input image, the aspect ratio parameters, the image processing requirement parameters (such as contrast enhancement effect, image noise processing requirements, color naturalness requirements, etc.), etc.

[0122] 103. For each image block, determine the initial brightness average function corresponding to the first sub-image block and the average value of the texture parameters corresponding to the second sub-image block in the image block, and perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block.

[0123] In the embodiment of the present invention, the target filtering operation includes a basic filtering operation and a spatial-domain guided filtering operation, and the spatial-domain guided filtering operation can be replaced by filtering methods such as mean filtering and bilateral filtering.

[0124] 104. For each image block, perform a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain a mapped image block, and perform a saturation processing operation on the mapped image block to obtain a target image block.

[0125] In an embodiment of the present invention, optionally, for each image block, brightness mapping and saturation processing operations can be directly performed on the image block, or an upsampling difference operation, such as bilinear interpolation, bicubic interpolation, or other non-fixed weight interpolation methods, can be first performed on the image block according to the resolution size of the image block to update the image block, and then brightness mapping and saturation processing operations can be performed on the image block.

[0126] 105. Determine the contrast-enhanced image corresponding to the original image based on all target image blocks.

[0127] In an embodiment of the present invention, optionally, all target image blocks after splicing can be directly determined as contrast-enhanced images corresponding to the original images, or all target image blocks can be first converted into RGB type image blocks, and then all converted image blocks after splicing can be determined as contrast-enhanced images corresponding to the original images.

[0128] It can be seen that the implementation of the embodiment of the present invention can achieve a local dynamic contrast enhancement process of the image by performing brightness layering, blocking, initial brightness averaging function filtering and post-processing operations on the original image. While retaining image details, the image contrast enhancement effect is improved, making the image appear natural, with low noise and excellent color performance, and also reducing computational complexity.

[0129] In an optional embodiment, determining the initial brightness average function corresponding to the first sub-image block in the image block in step 103 includes:

[0130] For each first pixel included in the first sub-image block in the image block, determining a multi-order orthogonal transformation function of the brightness value according to the brightness value of the first pixel, and determining a multi-order average orthogonal transformation function of the brightness value according to the multi-order orthogonal transformation function of the brightness value;

[0131] A multi-order average orthogonal transformation function of the brightness values ​​of all first pixels is determined as an initial brightness average function corresponding to the first sub-image block in the image block.

[0132] In this optional embodiment, for each image block, the brightness information of the first sub-image block and the texture information of the second sub-image block contained therein are independently counted. For each first pixel contained in the first sub-image block, the multi-order orthogonal transformation function of the brightness value of the first pixel is:

[0133]

[0134] I b is the brightness value of the first pixel, K is a preset normalization constant (which can be understood as the normalization constant of the cosine orthogonal basis), and i is the target order index parameter of the brightness value of the first pixel, where the value range of i is [0, N], and N is the fitting order of the preset maximum orthogonal basis polynomial.

[0135] And, the average value of the texture parameters corresponding to the second sub-image block is;

[0136]

[0137] T Ωis the total number of pixels in the second sub-image block Ω, and LP(x, y) is the residual value of the second pixel with coordinates (x, y) in the second sub-image block. Here, stLp needs to be normalized to [0, 1].

[0138] It can be seen that this optional embodiment can determine the initial brightness average function corresponding to the first sub-image block in each image block by determining the multi-order orthogonal transformation function of the brightness value of each first pixel contained in the first sub-image block. In this way, the reliability and accuracy of the analysis of the brightness information of the image block are improved, which is conducive to improving the subsequent filtering reliability and accuracy of the initial brightness average function of the image block, thereby helping to enhance the contrast enhancement effect of the image block.

[0139] In another optional embodiment, the target filtering operation is performed on the initial brightness average function corresponding to the first sub-image block by using the average value of the texture parameters corresponding to the second sub-image block in step 103 to obtain the target filtered function corresponding to the first sub-image block, including:

[0140] For each first pixel included in the first sub-image block, performing an indefinite integral operation on the multi-order orthogonal transformation function of the brightness value of the first pixel according to the multi-order orthogonal transformation function of the brightness value to obtain a multi-order target transformation function of the brightness value;

[0141] determining a cumulative probability distribution function corresponding to the first sub-image block based on a multi-order target transformation function of brightness values ​​of all first pixels in the first sub-image block and an initial brightness average function corresponding to the first sub-image block;

[0142] Through the average value of the texture parameters and the cumulative probability distribution function corresponding to the second sub-image block, a basic filtering operation is performed on the initial brightness average function corresponding to the first sub-image block to obtain the basic filtered brightness average function corresponding to the first sub-image block, and a spatial domain guided filtering operation is performed on the basic filtered brightness average function to obtain the target filtered function corresponding to the first sub-image block.

[0143] In this optional embodiment, for each first pixel included in the first sub-image block, the multi-order target transformation function of its brightness value is:

[0144]

[0145] And, the cumulative probability distribution function corresponding to the first sub-image block is:

[0146]

[0147] is the initial brightness average function corresponding to the first sub-image block, and M is the maximum brightness value under the bit width corresponding to the first sub-image block. The essence of is the histogram information of local image brightness.

[0148] Furthermore, M is the maximum brightness value under the bit width corresponding to the first sub-image block. It can be understood that when the first sub-image block is 8 bits, M=255; when the first sub-image block is 10 bits, M=1023.

[0149] Furthermore, usually, in order to speed up the processing, I b Sampling is performed at a certain interval, that is, it is not necessary to fit each grayscale completely. For example, when the first sub-image block is 8 bits, the number of sampling points can be reduced to 4 bits (17 points) or 5 bits (33 points).

[0150] It can be seen that this optional embodiment can determine the cumulative probability distribution function corresponding to the first sub-image block through the multi-order orthogonal transformation function of the brightness values ​​of all first pixels contained in the first sub-image block, and then perform target filtering operation on the initial brightness average function corresponding to the first sub-image block through the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function. In this way, the filtering reliability and accuracy of the initial brightness average function corresponding to the first sub-image block are improved, which is conducive to retaining the texture information of the image block, so that the details of the image block can be clearly displayed.

[0151] In yet another optional embodiment, the above step of performing a basic filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function to obtain the basic filtered brightness average function corresponding to the first sub-image block includes:

[0152] Performing a curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to an average value of texture parameters corresponding to the second sub-image block to obtain a first adjusted function corresponding to the first sub-image block;

[0153] Determining an approximate histogram distribution function corresponding to the first sub-image block according to the first adjusted function, and calculating a first before-and-after mapping brightness difference function corresponding to the first sub-image block according to the first adjusted function and the approximate histogram distribution function;

[0154] Determining a brightness guidance function corresponding to the first sub-image block according to the first before-after mapping brightness difference function, and determining a second before-after mapping brightness difference function corresponding to the first sub-image block according to the brightness guidance function and the first adjusted function;

[0155] Determining a mapping mixing coefficient corresponding to the first sub-image block according to the first before-and-after mapping brightness difference function and the second before-and-after mapping brightness difference function, and determining a brightness mixing mapping function corresponding to the first sub-image block according to the mapping mixing coefficient, the brightness guide function, and the first adjusted function;

[0156] According to the preset curve restriction area, the brightness mixing mapping function is interval-amplitude restricted to obtain the restricted mapping function corresponding to the first sub-image block, and the basic filtered brightness average function corresponding to the first sub-image block is fitted through the restricted mapping function and the multi-order target transformation function of the brightness values ​​of all first pixels in the first sub-image block.

[0157] In this optional embodiment, the basic filtering process includes curve texture adjustment, curve guide adjustment, curve amplitude limitation and LPF fitting operations.

[0158] Furthermore, the first adjusted function corresponding to the first sub-image block is:

[0159] C′(I b )=stLp*C(I b )+(1-stLp)I b ;

[0160] The curve texture adjustment process can make the enhancement effect of relatively flat areas of the image block weaker than that of textured areas, so as to reduce the noise in the flat areas.

[0161] Furthermore, the approximate histogram distribution function corresponding to the first sub-image block is:

[0162] H(I b )=C′(I b +1)-C′(I b ).

[0163] And, the brightness difference function before and after the first mapping corresponding to the first sub-image block is:

[0164]

[0165] And, the brightness guidance function corresponding to the first sub-image block is:

[0166]

[0167] And, the brightness difference function before and after the second mapping corresponding to the first sub-image block is:

[0168]

[0169] And, the mapping mixing coefficient corresponding to the first sub-image block is:

[0170]

[0171] And, the brightness mixing mapping function corresponding to the first sub-image block is:

[0172] C″(I b )=α*C′(I b )+(1-α)G(I b ).

[0173] It should be noted that by determining the brightness mixing mapping function corresponding to the first sub-image block through the curve-guided adjustment process, it can be ensured that the mapping curve corresponding to the first sub-image block can maintain the same brightness before and after mapping.

[0174] Furthermore, by limiting the interval amplitude of the brightness mixing mapping function, the steepness of the mapping curve corresponding to the first sub-image block can be limited, and the curve limit area can be as follows: Figure 5 In this closed quadrilateral area, y1=ax1 is the dark part pull-down limit line, a is the slope of the dark part pull-down limit line, and its value range is [0, 1]; y2=1-b(1-x2) is the bright part pull-down limit line, b is the slope of the bright part pull-down limit line, and its value range is [1, +∞]; y3=cx3 is the dark part pull-up limit line, c is the slope of the dark part pull-up limit line, and its value range is [1, +∞]; y4=1-d(1-x4) is the bright part pull-up limit line, d is the slope of the bright part pull-down limit line, and its value range is [0, 1].

[0175] Furthermore, the least squares method can be used to fit the basic filtered brightness average function corresponding to the first sub-image block. The conversion process is as follows: As mentioned above, the expression from LPF to mapping curve is Let A i represent The above expression can be expressed in matrix form as follows:

[0176] Q M×N ×A N×1 =C M×1

[0177] Where M represents the number of pixel grayscales, N is the order of the orthogonal polynomial, and Q is the indefinite integral of the orthogonal transformation basis P mentioned above. The value of Q is fixed within the domain of definition. The above expression can be simplified to:

[0178] Q×A=C.

[0179] Therefore, the above problem is transformed into, when C and Q are known, we need to find the corresponding A i , which is a typical linear equations problem. For the above expression, multiply both sides by QT ,have:

[0180] Q T QA=Q T C;

[0181] Among them, Q T is the transposed matrix of matrix Q, Q T The result of Q is a square matrix. Therefore, solving the matrix A is transformed into:

[0182] A=inv(Q T Q)·Q T C.

[0183] Among them, inv(..) is the MATLAB matrix inversion function. If Q T If the Q matrix is ​​invertible, the result is the inverse matrix; if the matrix is ​​not invertible, the result is the least squares result. Let W = inv(Q T Q)·Q T , then the expression converted from the mapping curve C back to LPF is as follows:

[0184] LPF=W×C.

[0185] Since the transformation matrix W does not change over time, it can be calculated in advance in practical applications and applied by looking up the table. The basic filtering is then continued to complete the spatial domain guided filtering.

[0186] It can be seen that this optional embodiment can perform curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to the average value of the texture parameters corresponding to the second sub-image block, and then calculate the brightness difference function before and after the first mapping corresponding to the first sub-image block based on the obtained first adjusted function corresponding to the first sub-image block, so as to perform brightness mapping adjustment on it, and obtain the restricted mapping function corresponding to the first sub-image block, so as to fit the basic filtered brightness average function corresponding to the first sub-image block. In this way, the local texture features of the image can be dynamically responded to during the filtering process, and the problem of detail loss or over-smoothing caused by traditional global filtering can be reduced, thereby improving the detail retention ability in complex texture areas; at the same time, it can also effectively maintain the consistency of the overall brightness distribution of the image, and significantly improve visual comfort.

[0187] In yet another optional embodiment, a spatial domain guided filtering operation is performed on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block, including:

[0188] Calculating the intra-window brightness average function of the first sub-image block and other first sub-image blocks in the target window according to the preset window parameters of the target window and the basic filtered brightness average function;

[0189] Calculating a brightness variance parameter corresponding to the first sub-image block based on the basic filtered brightness average function and the brightness average function within the window, and determining a brightness weighting coefficient corresponding to the first sub-image block based on the brightness variance parameter and a preset filter coefficient;

[0190] A target filtered function corresponding to the first sub-image block is determined according to the brightness weighting coefficient, the basic filtered brightness average function, and the brightness average function within the window.

[0191] In this optional embodiment, it can be understood that the current first sub-image block and H*L first sub-image blocks around it are traversed to implement the filtering operation of multiple first sub-image blocks.

[0192] Among them, the brightness average function within the window is:

[0193]

[0194] H is the first side length parameter in the window parameter, L is the second side length parameter in the window parameter, h is the first side length index parameter of the window corresponding to the first sub-image block, l is the second side length index parameter of the window corresponding to the first sub-image block, is the basic filtered brightness average function corresponding to the first sub-image block.

[0195] And, the brightness variance parameter corresponding to the first sub-image block is:

[0196]

[0197] And, the brightness weighting coefficient corresponding to the first sub-image block is:

[0198]

[0199] Among them, δ is the filtering coefficient. The larger the value of δ is, the stronger the filtering effect is.

[0200] And, the target filtered function corresponding to the first sub-image block is:

[0201]

[0202] Furthermore, if the original image is a video frame image and the timing is not allowed, since the difference between frames in the image video is relatively small, the It can also serve as the next video frame image

[0203] It can be seen that this optional embodiment can realize the process of adaptively adjusting the filter intensity according to the brightness distribution characteristics of the local area of ​​the image by calculating the brightness average function within the target window, so that the target filtered function can more accurately fit the brightness distribution characteristics of the original image, effectively avoiding the detail blurring problem caused by global filtering, and enhancing the local contrast and edge details of the image; at the same time, through the linkage calculation of the brightness variance parameter and the filter coefficient, differentiated processing of different brightness distribution areas in the image is achieved, such as using a stronger smoothing filter to suppress noise in high brightness variance areas, while retaining detailed textures by reducing the filter intensity in low variance areas, thereby achieving a dynamic balance between noise reduction and detail retention. In addition, the calculation process of the present invention is low in complexity, which is conducive to ensuring the real-time performance of image contrast enhancement.

[0204] In yet another optional embodiment, the step 104 above performs a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain the mapped image block, including:

[0205] Calculating an initial brightness mapping value corresponding to each first pixel according to a target filtered function corresponding to the first sub-image block, a multi-order target transformation function of the brightness value of each first pixel in the first sub-image block, and a pre-acquired low-frequency brightness component of each first pixel;

[0206] For each first pixel in the first sub-image block, calculating a mixed brightness mapping value corresponding to the first pixel based on an initial brightness mapping value corresponding to the first pixel, a low-frequency brightness component, and a preset intensity coefficient, and calculating a target brightness mapping value corresponding to the first pixel based on the mixed brightness mapping value corresponding to the first pixel, a residual value of the corresponding target second pixel, and a preset detail magnification coefficient;

[0207] According to the target brightness mapping values ​​corresponding to all first pixels in the first sub-image block, a brightness mapping operation is performed on the image block to obtain a mapped image block.

[0208] In this optional embodiment, the target second pixel is a second pixel included in the second sub-image block in the image block and having the same pixel coordinates as the first pixel.

[0209] Furthermore, for each first pixel in the first sub-image block, the initial brightness mapping value corresponding to the first pixel is:

[0210]

[0211] I is the low-frequency brightness component corresponding to the first pixel.

[0212] And the mixed brightness mapping value corresponding to the first pixel is:

[0213] I fus =(1-γ)*I eq +γ*I;

[0214] γ is the intensity coefficient.

[0215] And, the target brightness mapping value corresponding to the first pixel is:

[0216] I out =I fus +acc*LP;

[0217] acc is the detail magnification coefficient, and LP is the residual value of the second pixel of the target.

[0218] It should be noted that γ is an externally configured intensity coefficient that takes different values ​​depending on the input low-frequency brightness (ie, the low-frequency brightness component of the corresponding first pixel). eq To perform brightness intensity mixing output, we get I fus , which can effectively reduce the situation of over-enhancement of the image. And, through the acc detail amplification coefficient, the image details can be appropriately weakened or enhanced.

[0219] It can be seen that this optional embodiment can further balance the global and local brightness mapping intensities of the image through the target filtered function corresponding to the first sub-image block, the multi-order target transformation function of the pixel brightness value, the pixel low-frequency brightness component and the introduced intensity coefficient, thereby ensuring that the image brightness transition is natural and the layers are distinct; in addition, by further utilizing the residual value and detail magnification coefficient of the target second pixel, the image texture information can be enhanced in a targeted manner, so that the image still maintains sharpness after the brightness is increased, thereby improving the image visual effect.

[0220] Example 2

[0221] See also Figure 2 , Figure 2 FIG. 1 is a flow chart of another method for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention. Figure 2 The described method for enhancing local dynamic contrast of images can be applied to a variety of digital images for local dynamic contrast enhancement, such as photos, video frames, medical images, remote sensing images, scanned images, computer graphics, etc., which is not limited in the embodiments of the present invention. Optionally, the method can be implemented by an image contrast enhancement device, which can be integrated into an image processing device, such as a smart computer, smart phone, tablet, camera device, driving recorder, etc., or a local server or cloud server for processing the local dynamic contrast enhancement process of images, which is not limited in the embodiments of the present invention. Figure 2 As shown, the method for enhancing local dynamic contrast of an image may include the following operations:

[0222] 201. Perform a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image.

[0223] 202. Perform a block operation on the layered image to obtain multiple image blocks corresponding to the layered image; each image block includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image.

[0224] 203. For each image block, determine the initial brightness average function corresponding to the first sub-image block and the average value of the texture parameters corresponding to the second sub-image block in the image block, and perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block.

[0225] 204. For each image block, perform a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain a mapped image block.

[0226] 205. For each image block, calculate a first saturation parameter of the image block and a second saturation parameter of the mapped image block, and calculate a saturation compensation gain parameter corresponding to the mapped image block based on the first saturation parameter, the second saturation parameter and a preset saturation enhancement coefficient.

[0227] In the embodiment of the present invention, the saturation compensation gain parameter corresponding to the mapped image block is:

[0228]

[0229] ACC satu is the saturation enhancement coefficient (which can control the image color performance), S bf is the first saturation parameter, S af is the second saturation parameter.

[0230] Furthermore, S bf With S af Both can be achieved through image segmentation and the RGB space conversion process of the mapped image segmentation and the saturation calculation formula: To calculate.

[0231] Also, it should be noted that if the original image is a grayscale image, there is no need to execute steps 205 to 209 (i.e., no saturation processing is required), and the contrast-enhanced image corresponding to the original image can be directly determined based on all the mapped image blocks after splicing; if the original image is a color image, steps 205 to 209 need to be executed.

[0232] 206. For each image block, determine the maximum blue difference compensation gain parameter corresponding to the image block after mapping based on the blue difference chromaticity component parameter of the image block, and determine the maximum red difference compensation gain parameter corresponding to the image block after mapping based on the red difference chromaticity component parameter of the image block.

[0233] In the embodiment of the present invention, it should be noted that in order to prevent the UV value after saturation enhancement from crossing the boundary (outside the bit width range), the saturation gain needs to be limited. Taking the V component of the image block as an example, the maximum red difference compensation gain parameter v_gain needs to meet the following constraints: 0≤V*v_gain+0.5≤1, that is (V red difference chromaticity component parameter), that is, the maximum red difference compensation gain parameter v_gain is Similarly, the value of the maximum blue difference compensation gain parameter u_gain can be obtained.

[0234] 207. For each image block, determine the compensation gain limit parameter corresponding to the mapped image block based on the saturation compensation gain parameter, the maximum blue difference compensation gain parameter, and the maximum red difference compensation gain parameter, and determine the target blue difference compensation gain parameter and the target red difference compensation gain parameter corresponding to the mapped image block based on the compensation gain limit parameter, the blue difference chroma component parameter, and the red difference chroma component parameter.

[0235] In the embodiment of the present invention, the compensation gain limit parameter corresponding to the mapped image block is:

[0236] gain=Min(uv_gain, u_gain, v_gain);

[0237] u_gain is the maximum blue difference compensation gain parameter, and v_gain is the maximum red difference compensation gain parameter.

[0238] And, the target blue difference compensation gain parameters and target red difference compensation gain parameters corresponding to the mapped image blocks are:

[0239] Uˋ=U*gain, Vˋ=V*gain;

[0240] U is the blue difference chrominance component parameter, and V is the red difference chrominance component parameter.

[0241] 208. For each image block, perform a saturation processing operation on the mapped image block according to the target blue difference compensation gain parameter and the target red difference compensation gain parameter to obtain a target image block.

[0242] In the embodiments of the present invention, it should be noted that because the YUV color space has narrow ranges at the top and bottom and a wide range in the middle, the saturation spatial range varies significantly at different brightness levels. Furthermore, after the brightness changes after local contrast enhancement, the original saturation will also change with the brightness change. Therefore, it is necessary to perform saturation compensation or enhancement based on the difference between the output brightness and the input brightness to maintain good image color rendering.

[0243] 209. Determine a contrast-enhanced image corresponding to the original image based on all target image blocks.

[0244] In the embodiment of the present invention, for other descriptions of steps 201 to 204 and step 209, please refer to the detailed description of steps 101 to 105 in the first embodiment, which will not be repeated in the embodiment of the present invention.

[0245] It can be seen that the implementation of the embodiment of the present invention can compensate or enhance saturation through the difference between the output brightness and input brightness of the image block, which can maintain the good color performance of the image block, so that the image effect of the final contrast-enhanced image is more natural, and the situation where the saturation changes with the brightness change is reduced, which is conducive to further improving the visual effect of the contrast-enhanced image.

[0246] Example 3

[0247] See also Figure 3 , Figure 3 FIG. 1 is a schematic diagram of the structure of a device for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention. Figure 3 As shown, the image local dynamic contrast enhancement device may include:

[0248] The layering module 301 is used to perform a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image;

[0249] A blocking module 302 is configured to perform a blocking operation on the layered image to obtain a plurality of image blocks corresponding to the layered image; each image block includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image;

[0250] A filtering module 303 is configured to determine, for each image block, an initial brightness average function corresponding to a first sub-image block and an average value of texture parameters corresponding to a second sub-image block in the image block, and perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block;

[0251] A post-processing module 304 is configured to perform a brightness mapping operation on each image block using a target filtered function corresponding to the first sub-image block to obtain a mapped image block, and to perform a saturation processing operation on the mapped image block to obtain a target image block;

[0252] The determination module 305 is configured to determine the contrast-enhanced image corresponding to the original image according to all target image blocks.

[0253] It can be seen that implementation Figure 3 The described image local dynamic contrast enhancement device can realize the local dynamic contrast enhancement process of the image by performing brightness layering, blocking, initial brightness average function filtering and post-processing operations on the original image. While retaining the image details, it improves the image contrast enhancement effect, makes the image appear natural, has low noise, and has excellent color performance, and also reduces the computational complexity.

[0254] In an optional embodiment, the manner in which the filtering module 303 determines the initial brightness average function corresponding to the first sub-image block in the image block specifically includes:

[0255] For each first pixel included in the first sub-image block in the image block, determining a multi-order orthogonal transformation function of the brightness value according to the brightness value of the first pixel, and determining a multi-order average orthogonal transformation function of the brightness value according to the multi-order orthogonal transformation function of the brightness value;

[0256] A multi-order average orthogonal transformation function of the brightness values ​​of all first pixels is determined as an initial brightness average function corresponding to the first sub-image block in the image block.

[0257] In this optional embodiment, for each first pixel included in the first sub-image block, the multi-order orthogonal transformation function of the brightness value of the first pixel is:

[0258]

[0259] I b is the brightness value of the first pixel, K is a preset normalization constant, i is a target order index parameter of the brightness value of the first pixel, wherein the value range of i is [0, N], and N is the fitting order of the preset maximum orthogonal basis polynomial;

[0260] And, the average value of the texture parameters corresponding to the second sub-image block is;

[0261]

[0262] T Ω is the total number of pixels in the second sub-image block Ω, and LP(x, y) is the residual value of the second pixel with pixel coordinates (x, y) in the second sub-image block.

[0263] It can be seen that implementation Figure 3 The described image local dynamic contrast enhancement device can determine the initial brightness average function corresponding to the first sub-image block in each image block by determining the multi-order orthogonal transformation function of the brightness value of each first pixel contained in the first sub-image block. In this way, the reliability and accuracy of the analysis of the brightness information of the image block are improved, which is conducive to improving the subsequent filtering reliability and accuracy of the initial brightness average function of the image block, thereby helping to improve the contrast enhancement effect of the image block.

[0264] In another optional embodiment, the filtering module 303 performs a target filtering operation on the initial brightness average function corresponding to the first sub-image block by using the average value of the texture parameters corresponding to the second sub-image block, and obtains the target filtered function corresponding to the first sub-image block in a manner specifically including:

[0265] For each first pixel included in the first sub-image block, performing an indefinite integral operation on the multi-order orthogonal transformation function of the brightness value of the first pixel according to the multi-order orthogonal transformation function of the brightness value to obtain a multi-order target transformation function of the brightness value;

[0266] determining a cumulative probability distribution function corresponding to the first sub-image block based on a multi-order target transformation function of brightness values ​​of all first pixels in the first sub-image block and an initial brightness average function corresponding to the first sub-image block;

[0267] Through the average value of the texture parameters and the cumulative probability distribution function corresponding to the second sub-image block, a basic filtering operation is performed on the initial brightness average function corresponding to the first sub-image block to obtain the basic filtered brightness average function corresponding to the first sub-image block, and a spatial domain guided filtering operation is performed on the basic filtered brightness average function to obtain the target filtered function corresponding to the first sub-image block.

[0268] In this optional embodiment, the multi-order target transformation function of the brightness value is:

[0269]

[0270] And, the cumulative probability distribution function corresponding to the first sub-image block is:

[0271]

[0272] is the initial brightness average function corresponding to the first sub-image block, and M is the maximum brightness value under the bit width corresponding to the first sub-image block.

[0273] It can be seen that implementation Figure 3The described image local dynamic contrast enhancement device can determine the cumulative probability distribution function corresponding to the first sub-image block through the multi-order orthogonal transformation function of the brightness values ​​of all first pixels contained in the first sub-image block, and then perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block through the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function. In this way, the filtering reliability and accuracy of the initial brightness average function corresponding to the first sub-image block are improved, which is conducive to retaining the texture information of the image block, so that the details of the image block can be clearly displayed.

[0274] In another optional embodiment, the filtering module 303 performs a basic filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function to obtain the basic filtered brightness average function corresponding to the first sub-image block. Specifically, the method includes:

[0275] Performing a curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to an average value of texture parameters corresponding to the second sub-image block to obtain a first adjusted function corresponding to the first sub-image block;

[0276] Determining an approximate histogram distribution function corresponding to the first sub-image block according to the first adjusted function, and calculating a first before-and-after mapping brightness difference function corresponding to the first sub-image block according to the first adjusted function and the approximate histogram distribution function;

[0277] Determining a brightness guidance function corresponding to the first sub-image block according to the first before-after mapping brightness difference function, and determining a second before-after mapping brightness difference function corresponding to the first sub-image block according to the brightness guidance function and the first adjusted function;

[0278] Determining a mapping mixing coefficient corresponding to the first sub-image block according to the first before-and-after mapping brightness difference function and the second before-and-after mapping brightness difference function, and determining a brightness mixing mapping function corresponding to the first sub-image block according to the mapping mixing coefficient, the brightness guide function, and the first adjusted function;

[0279] According to the preset curve restriction area, the brightness mixing mapping function is interval-amplitude restricted to obtain the restricted mapping function corresponding to the first sub-image block, and the basic filtered brightness average function corresponding to the first sub-image block is fitted through the restricted mapping function and the multi-order target transformation function of the brightness values ​​of all first pixels in the first sub-image block.

[0280] In this optional embodiment, the first adjusted function corresponding to the first sub-image block is:

[0281] C′(I b)=stLp*C(I b )+(1-stLp)I b ;

[0282] The approximate histogram distribution function corresponding to the first sub-image block is:

[0283] H(I b )=C′(I b +1)-C′(I b );

[0284] The brightness difference function before and after the first mapping corresponding to the first sub-image block is:

[0285]

[0286] The brightness guidance function corresponding to the first sub-image block is:

[0287]

[0288] The brightness difference function before and after the second mapping corresponding to the first sub-image block is:

[0289]

[0290] The mapping mixing coefficient corresponding to the first sub-image block is:

[0291]

[0292] The brightness mixing mapping function corresponding to the first sub-image block is:

[0293] C″(I b )=α*C′(I b )+(1-α)G(I b ).

[0294] It can be seen that implementation Figure 3 The described image local dynamic contrast enhancement device can perform curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to the average value of the texture parameters corresponding to the second sub-image block, and then calculate the brightness difference function before and after the first mapping corresponding to the first sub-image block based on the obtained first adjusted function corresponding to the first sub-image block, thereby performing brightness mapping adjustment on it, and obtaining the restricted mapping function corresponding to the first sub-image block, so as to fit the basic filtered brightness average function corresponding to the first sub-image block. In this way, the local texture features of the image can be dynamically responded to during the filtering process, reducing the problem of detail loss or over-smoothing caused by traditional global filtering, thereby improving the detail retention ability in complex texture areas; at the same time, it can also effectively maintain the consistency of the overall brightness distribution of the image, and significantly improve visual comfort.

[0295] In another optional embodiment, the filtering module 303 performs a spatial domain guided filtering operation on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block, specifically including:

[0296] Calculating the intra-window brightness average function of the first sub-image block and other first sub-image blocks in the target window according to the preset window parameters of the target window and the basic filtered brightness average function;

[0297] Calculating a brightness variance parameter corresponding to the first sub-image block based on the basic filtered brightness average function and the brightness average function within the window, and determining a brightness weighting coefficient corresponding to the first sub-image block based on the brightness variance parameter and a preset filter coefficient;

[0298] A target filtered function corresponding to the first sub-image block is determined according to the brightness weighting coefficient, the basic filtered brightness average function, and the brightness average function within the window.

[0299] In this optional embodiment, the brightness average function within the window is:

[0300]

[0301] H is the first side length parameter in the window parameter, L is the second side length parameter in the window parameter, h is the first side length index parameter of the window corresponding to the first sub-image block, l is the second side length index parameter of the window corresponding to the first sub-image block, is the basic filtered brightness average function corresponding to the first sub-image block;

[0302] And, the brightness variance parameter corresponding to the first sub-image block is:

[0303]

[0304] The brightness weighting coefficient corresponding to the first sub-image block is:

[0305]

[0306] Among them, δ is the filter coefficient;

[0307] The target filtered function corresponding to the first sub-image block is:

[0308]

[0309] It can be seen that implementation Figure 3The described local dynamic contrast enhancement device for an image can adaptively adjust the filter strength according to the brightness distribution characteristics of the local area of ​​the image by calculating the brightness average function within the target window. This allows the target filtered function to more accurately fit the brightness distribution characteristics of the original image, effectively avoiding the detail blurring problem caused by global filtering, and enhancing the local contrast and edge details of the image. At the same time, through the linked calculation of the brightness variance parameter and the filter coefficient, differentiated processing is achieved for different brightness distribution areas in the image. For example, in high brightness variance areas, a stronger smoothing filter is used to suppress noise, while in low variance areas, the filter strength is reduced to retain detailed texture, thereby achieving a dynamic balance between noise reduction and detail preservation. In addition, the computational process of the present invention is low in complexity, which is conducive to ensuring the real-time performance of image contrast enhancement.

[0310] In another optional embodiment, the post-processing module 304 performs a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain the mapped image block. Specifically, the method includes:

[0311] Calculating an initial brightness mapping value corresponding to each first pixel according to a target filtered function corresponding to the first sub-image block, a multi-order target transformation function of the brightness value of each first pixel in the first sub-image block, and a pre-acquired low-frequency brightness component of each first pixel;

[0312] For each first pixel in the first sub-image block, calculating a mixed brightness mapping value corresponding to the first pixel based on an initial brightness mapping value corresponding to the first pixel, a low-frequency brightness component, and a preset intensity coefficient, and calculating a target brightness mapping value corresponding to the first pixel based on the mixed brightness mapping value corresponding to the first pixel, a residual value of the corresponding target second pixel, and a preset detail magnification coefficient;

[0313] According to the target brightness mapping values ​​corresponding to all first pixels in the first sub-image block, a brightness mapping operation is performed on the image block to obtain a mapped image block.

[0314] In this optional embodiment, the target second pixel is a second pixel included in the second sub-image block in the image block and having the same pixel coordinates as the first pixel.

[0315] For each first pixel in the first sub-image block, the initial brightness mapping value corresponding to the first pixel is:

[0316]

[0317] I is the low-frequency brightness component corresponding to the first pixel;

[0318] And the mixed brightness mapping value corresponding to the first pixel is:

[0319] I fus =(1-γ)*I eq +γ*I;

[0320] γ is the intensity coefficient;

[0321] And, the target brightness mapping value corresponding to the first pixel is:

[0322] I out =I fus +acc*LP;

[0323] acc is the detail magnification coefficient, and LP is the residual value of the second pixel of the target.

[0324] It can be seen that implementation Figure 3 The described image local dynamic contrast enhancement device can further balance the global and local brightness mapping intensities of the image through the target filtered function corresponding to the first sub-image block, the multi-order target transformation function of the pixel brightness value, the pixel low-frequency brightness component and the introduced intensity coefficient, ensuring that the image brightness transition is natural and the layers are clear; in addition, the residual value and detail magnification coefficient of the target second pixel are further utilized to specifically enhance the image texture information, so that the image still maintains sharpness after the brightness is increased, thereby improving the image visual effect.

[0325] In another optional embodiment, the post-processing module 304 performs a saturation processing operation on the mapped image blocks to obtain target image blocks, specifically including:

[0326] Calculating a first saturation parameter of the image block and a second saturation parameter of the mapped image block, and calculating a saturation compensation gain parameter corresponding to the mapped image block based on the first saturation parameter, the second saturation parameter, and a preset saturation enhancement coefficient;

[0327] Determining a maximum blue difference compensation gain parameter corresponding to the image block after mapping based on the blue difference chromaticity component parameter of the image block, and determining a maximum red difference compensation gain parameter corresponding to the image block after mapping based on the red difference chromaticity component parameter of the image block;

[0328] Determine the compensation gain limit parameter corresponding to the mapped image block according to the saturation compensation gain parameter, the maximum blue difference compensation gain parameter, and the maximum red difference compensation gain parameter, and determine the target blue difference compensation gain parameter and the target red difference compensation gain parameter corresponding to the mapped image block according to the compensation gain limit parameter, the blue difference chroma component parameter, and the red difference chroma component parameter;

[0329] According to the target blue difference compensation gain parameter and the target red difference compensation gain parameter, a saturation processing operation is performed on the mapped image block to obtain the target image block.

[0330] In this optional embodiment, the saturation compensation gain parameter corresponding to the mapped image block is:

[0331]

[0332] ACC satu is the saturation enhancement coefficient, S bf is the first saturation parameter, S af is the second saturation parameter;

[0333] And, the compensation gain limit parameters corresponding to the mapped image blocks are:

[0334] gain=Min(uv_gain, u_gain, v_gain);

[0335] u_gain is the maximum blue difference compensation gain parameter, v_gain is the maximum red difference compensation gain parameter;

[0336] And, the target blue difference compensation gain parameters and target red difference compensation gain parameters corresponding to the mapped image blocks are:

[0337] U`=U*gain,V`=V*gain;

[0338] U is the blue difference chrominance component parameter, and V is the red difference chrominance component parameter.

[0339] It can be seen that implementation Figure 3 The described local dynamic contrast enhancement device for an image can compensate or enhance saturation by using the difference between the output brightness and input brightness of an image block, thereby maintaining good color performance of the image block, making the image effect of the final contrast-enhanced image more natural, and reducing the situation where saturation changes inappropriately with brightness changes, thereby facilitating further improvement of the visual effect of the contrast-enhanced image.

[0340] Example 4

[0341] See also Figure 4 , Figure 4 FIG. 1 is a structural diagram of another device for enhancing local dynamic contrast of an image disclosed in an embodiment of the present invention. Figure 4 As shown, the image local dynamic contrast enhancement device may include:

[0342] A memory 401 storing executable program code;

[0343] a processor 402 coupled to the memory 401;

[0344] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the image local dynamic contrast enhancement method described in the first embodiment or the second embodiment of the present invention.

[0345] Example 5

[0346] An embodiment of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the method for enhancing local dynamic contrast of an image described in Embodiment 1 or Embodiment 2 of the present invention.

[0347] Example 6

[0348] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps of the image local dynamic contrast enhancement method described in Example 1 or Example 2.

[0349] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0350] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0351] Finally, it should be noted that the method and device for enhancing local dynamic contrast of an image disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are intended to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may be modified or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for enhancing local dynamic contrast of an image, characterized in that: The method comprises: Performing a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image; Performing a block operation on the layered image to obtain a plurality of image blocks corresponding to the layered image; each of the image blocks includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image; For each of the image blocks, determining an initial brightness average function corresponding to the first sub-image block and an average value of texture parameters corresponding to the second sub-image block in the image block, and performing a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block; For each of the image blocks, performing a brightness mapping operation on the image block using the target filtered function corresponding to the first sub-image block to obtain a mapped image block, and performing a saturation processing operation on the mapped image block to obtain a target image block; According to all the target image blocks, a contrast-enhanced image corresponding to the original image is determined.

2. The method for enhancing local dynamic contrast of an image according to claim 1, wherein: The determining of the initial brightness average function corresponding to the first sub-image block in the image block includes: For each first pixel included in the first sub-image block in the image block, determining a multi-order orthogonal transformation function of the brightness value according to the brightness value of the first pixel, and determining a multi-order average orthogonal transformation function of the brightness value according to the multi-order orthogonal transformation function of the brightness value; determining a multi-order average orthogonal transformation function of the brightness values ​​of all the first pixels as an initial brightness average function corresponding to the first sub-image block in the image block; Wherein, for each first pixel included in the first sub-image block, the multi-order orthogonal transformation function of the brightness value of the first pixel is: I b is the brightness value of the first pixel, K is a preset normalization constant, and i is a target order index parameter of the brightness value of the first pixel, wherein the value range of i is [0, N], and N is the fitting order of the preset maximum orthogonal basis polynomial; And, the average value of the texture parameters corresponding to the second sub-image block is; T Ω is the total number of pixels in the second sub-image block Ω, and LP(x, y) is the residual value of the second pixel with pixel coordinates (x, y) in the second sub-image block.

3. The method for enhancing local dynamic contrast of an image according to claim 2, wherein: The step of performing a target filtering operation on the initial brightness average function corresponding to the first sub-image block by using the average value of the texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block includes: For each first pixel included in the first sub-image block, performing an indefinite integral operation on the multi-order orthogonal transformation function of the brightness value of the first pixel according to the multi-order orthogonal transformation function of the brightness value to obtain a multi-order target transformation function of the brightness value; determining a cumulative probability distribution function corresponding to the first sub-image block based on a multi-order target transformation function of the brightness values ​​of all the first pixels in the first sub-image block and an initial brightness average function corresponding to the first sub-image block; performing a basic filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function to obtain a basic filtered brightness average function corresponding to the first sub-image block, and performing a spatial domain guided filtering operation on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block; The multi-order target transformation function of the brightness value is: And, the cumulative probability distribution function corresponding to the first sub-image block is: is the initial brightness average function corresponding to the first sub-image block, and M is the maximum brightness value under the bit width corresponding to the first sub-image block.

4. The method for enhancing local dynamic contrast of an image according to claim 3, wherein: The step of performing a basic filtering operation on the initial brightness average function corresponding to the first sub-image block by using the average value of the texture parameters corresponding to the second sub-image block and the cumulative probability distribution function to obtain the basic filtered brightness average function corresponding to the first sub-image block includes: performing curve texture adjustment on the cumulative probability distribution function corresponding to the first sub-image block according to the average value of the texture parameters corresponding to the second sub-image block to obtain a first adjusted function corresponding to the first sub-image block; Determining an approximate histogram distribution function corresponding to the first sub-image block according to the first adjusted function, and calculating a first before-and-after mapping brightness difference function corresponding to the first sub-image block according to the first adjusted function and the approximate histogram distribution function; Determining a brightness guidance function corresponding to the first sub-image block according to the first before-after mapping brightness difference function, and determining a second before-after mapping brightness difference function corresponding to the first sub-image block according to the brightness guidance function and the first adjusted function; determining a mapping mixing coefficient corresponding to the first sub-image block according to the first before-and-after mapping luminance difference function and the second before-and-after mapping luminance difference function, and determining a luminance mixing mapping function corresponding to the first sub-image block according to the mapping mixing coefficient, the luminance guide function, and the first adjusted function; performing interval amplitude restriction on the brightness mixing mapping function according to a preset curve restriction region to obtain a restricted mapping function corresponding to the first sub-image block, and fitting a basic filtered brightness average function corresponding to the first sub-image block using the restricted mapping function and a multi-order target transformation function of the brightness values ​​of all the first pixels in the first sub-image block; The first adjusted function corresponding to the first sub-image block is: C′(I b )=stLp*C(I b )+(1-stLp)I b ; The approximate histogram distribution function corresponding to the first sub-image block is: H(I b )=C′(I b +1)-C′(I b ); The brightness difference function before and after the first mapping corresponding to the first sub-image block is: The brightness guidance function corresponding to the first sub-image block is: The brightness difference function before and after the second mapping corresponding to the first sub-image block is: The mapping mixing coefficient corresponding to the first sub-image block is: The brightness mixing mapping function corresponding to the first sub-image block is: C″(I b )=α*C′(I b )+(1-α)G(I b )。 5. The method for enhancing local dynamic contrast of an image according to claim 3, wherein: The performing of a spatial domain guided filtering operation on the basic filtered brightness average function to obtain a target filtered function corresponding to the first sub-image block includes: Calculating, according to preset window parameters of the target window and the basic filtered brightness average function, the brightness average function within the window corresponding to the first sub-image block and other first sub-image blocks within the target window; Calculating a brightness variance parameter corresponding to the first sub-image block according to the basic filtered brightness average function and the windowed brightness average function, and determining a brightness weighting coefficient corresponding to the first sub-image block according to the brightness variance parameter and a preset filter coefficient; Determining a target filtered function corresponding to the first sub-image block according to the brightness weighting coefficient, the basic filtered brightness average function, and the windowed brightness average function; The brightness average function within the window is: H is the first side length parameter in the window parameters, L is the second side length parameter in the window parameters, h is the first side length index parameter of the window corresponding to the first sub-image block, l is the second side length index parameter of the window corresponding to the first sub-image block, is the basic filtered brightness average function corresponding to the first sub-image block; And, the brightness variance parameter corresponding to the first sub-image block is: The brightness weighting coefficient corresponding to the first sub-image block is: Wherein, δ is the filtering coefficient; The target filtered function corresponding to the first sub-image block is:

6. The method for enhancing local dynamic contrast of an image according to claim 5, wherein: The step of performing a brightness mapping operation on the image block by using the target filtered function corresponding to the first sub-image block to obtain a mapped image block includes: Calculating an initial brightness mapping value corresponding to each first pixel according to a target filtered function corresponding to the first sub-image block, a multi-order target transformation function of the brightness value of each first pixel in the first sub-image block, and a pre-acquired low-frequency brightness component of each first pixel; For each first pixel in the first sub-image block, calculating a mixed brightness mapping value corresponding to the first pixel based on an initial brightness mapping value, a low-frequency brightness component, and a preset intensity coefficient corresponding to the first pixel, and calculating a target brightness mapping value corresponding to the first pixel based on the mixed brightness mapping value corresponding to the first pixel, a residual value of a corresponding target second pixel, and a preset detail magnification coefficient; the target second pixel being a second pixel included in the second sub-image block in the image block and having the same pixel coordinates as the first pixel; performing a brightness mapping operation on the image block according to target brightness mapping values ​​corresponding to all the first pixels in the first sub-image block to obtain a mapped image block; For each of the first pixels in the first sub-image block, the initial brightness mapping value corresponding to the first pixel is: I is the low-frequency brightness component corresponding to the first pixel; And, the mixed brightness mapping value corresponding to the first pixel is: I fus =(1-γ)*I eq +γ*I; γ is the intensity coefficient; And, the target brightness mapping value corresponding to the first pixel is: I out =I fus +acc*LP; acc is the detail magnification coefficient, and LP is the residual value of the target second pixel.

7. The method for enhancing local dynamic contrast of an image according to any one of claims 1 to 6, characterized in that: The performing a saturation processing operation on the mapped image block to obtain a target image block includes: Calculating a first saturation parameter of the image block and a second saturation parameter of the mapped image block, and calculating a saturation compensation gain parameter corresponding to the mapped image block based on the first saturation parameter, the second saturation parameter, and a preset saturation enhancement coefficient; Determining a maximum blue difference compensation gain parameter corresponding to the mapped image block according to the blue difference chroma component parameter of the image block, and determining a maximum red difference compensation gain parameter corresponding to the mapped image block according to the red difference chroma component parameter of the image block; Determining a compensation gain limit parameter corresponding to the mapped image block according to the saturation compensation gain parameter, the maximum blue difference compensation gain parameter, and the maximum red difference compensation gain parameter, and determining a target blue difference compensation gain parameter and a target red difference compensation gain parameter corresponding to the mapped image block according to the compensation gain limit parameter, the blue difference chroma component parameter, and the red difference chroma component parameter; performing a saturation processing operation on the mapped image block according to the target blue difference compensation gain parameter and the target red difference compensation gain parameter to obtain a target image block; The saturation compensation gain parameter corresponding to the mapped image block is: ACC satu is the saturation enhancement coefficient, S bf is the first saturation parameter, S af is the second saturation parameter; And, the compensation gain limit parameter corresponding to the mapped image block is: gain=Min(uv_gain, u_gain, v_gain); u_gain is the maximum blue difference compensation gain parameter, and v_gain is the maximum red difference compensation gain parameter; And, the target blue difference compensation gain parameter and the target red difference compensation gain parameter corresponding to the mapped image block are respectively: U`=U*gain,V`=V*gain; U is the blue difference chrominance component parameter, and V is the red difference chrominance component parameter.

8. A device for enhancing local dynamic contrast of an image, characterized in that: The device comprises: A layering module, configured to perform a brightness layering operation on the original image to be enhanced to obtain a layered image; the layered image includes a base layer image and a residual layer image; a blocking module configured to perform a blocking operation on the layered image to obtain a plurality of image blocks corresponding to the layered image; each of the image blocks includes a first sub-image block corresponding to the base layer image and a second sub-image block corresponding to the residual layer image; a filtering module configured to determine, for each of the image blocks, an initial brightness average function corresponding to the first sub-image block and an average value of texture parameters corresponding to the second sub-image block in the image block, and perform a target filtering operation on the initial brightness average function corresponding to the first sub-image block using the average value of texture parameters corresponding to the second sub-image block to obtain a target filtered function corresponding to the first sub-image block; a post-processing module configured to perform a brightness mapping operation on each of the image blocks using a target filtered function corresponding to the first sub-image block to obtain a mapped image block, and to perform a saturation processing operation on the mapped image block to obtain a target image block; A determination module is used to determine the contrast-enhanced image corresponding to the original image based on all the target image blocks.

9. An image local dynamic contrast enhancement device, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the image local dynamic contrast enhancement method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the image local dynamic contrast enhancement method according to any one of claims 1 to 7.

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